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IBI: Identification of Biomarker Genes in Individual Tumor Samples

  • School of Computer Science and Technology, Harbin Institute of Technology

Research output: Contribution to journalArticlepeer-review

Abstract

Individual patient biomarkers have an important role in personalized treatment. Although various high-throughput sequencing technologies are widely used in biological experiments, these are usually conducted only once or a few times for each patient, which makes it a challenging problem to identify biomarkers in individual patients. At present, there is a lack of effective methods to identify biomarkers in individual sample data. Here, we propose a novel method, IBI, to identify biomarkers in individual tumor samples. Experimental results from several tumor data sets showed that the proposed method could effectively find biomarker genes for individual patients, including common biomarkers related to the mechanisms of the development of cancer, which can be used to predict survival and drug response in patients. In summary, these results demonstrate that the proposed method offers a new perspective for analyzing individual samples.

Original languageEnglish
Article number1236
JournalFrontiers in Genetics
Volume10
DOIs
StatePublished - 26 Nov 2019
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • biomarker
  • gene expression data
  • individual sample
  • regression model
  • tumor

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